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When a new EHR system gets selected, the focus of data governance teams quickly shifts to the topic of medical data conversion.
And, those who have been through an application-to-application clinical data transition know that discrete EHR conversion can come with challenging data mapping issues. The difficulty lies in transforming and loading clinical information from a source system to a destination system when the destination system represents formatted source system data in a different context. That’s why EMR data conversion services are so specialized and critical. You only get one chance to ensure the integrity of your clinical data when it migrates from one EHR to another, so, it must be right. Lives depend on it.
Harmony Healthcare IT, an industry leader in data management, has been ranked as the top data extraction and migration healthcare IT company according Black Book™ Rankings, a division of Black Book™ Market Research. For over a decade, we have specialized in both discrete and non-discrete EMR and ERP data conversion for healthcare delivery organizations. Our U.S.-based team of EMR conversion specialists have extracted and converted clinical, financial and business data from hundreds of ambulatory, acute, and ancillary EHR and ERP software brands, such as Epic and Oracle Cerner. We tackle the complexity and variability of the EHR and ERP conversion process with our systematic approach, detailed planning, and decades of clinical data conversion experience.
When approaching a new data conversion opportunity, we like to invest in the upfront discovery and planning to better understand the bigger picture. This really helps us dig in to really understand all the details so we can scope a perfect solution for our clients things we like to dig into go forward system. First thing we like to understand what are those source systems that you’d like to convert data from? Are those source systems on premise? Are they third party vendor hosted? How can we help you get that data out? And we like to dig into timelines. Do you already have a go live date established? Do you have a timeline already developed by or proposed by the go forward vendor? If so, how can we plug right into that timeline to help with the solution from there? We like to understand the business needs. What’s the overall strategy by the business? What are the resource needs, those users, the clinical users, financial users, what are they doing every day? What are their workflows? What are their required data elements really digging in and understanding that from there, we truly try to understand the data elements and how they are stored in the legacy systems? Are they stored discretely? Are they documents? How are they gonna fit into the specifications provided by the go forward vendors? This all is helping shape, you know, again, that solution we start to get into the technical pieces. Like how are we gonna move the data? Is it gonna be secure drives that we ship? Is it gonna be secure file transfers? Can we even leverage replication servers to help move the data to minimize any data gaps that go live? So overall that upfront planning and discovery really helps us build out and architect a perfect solution for our clients.
Our enhanced data conversion offering, through a strategic relationship with DrFirst, employs artificial intelligence (AI) and machine learning (ML) to automate the process of migrating structured data from one EHR to another to inform clinical decision-making. Learn more.
In scoping and planning the data conversion, we typically start with the destination EHR go-live date and work backward, determining the timing of initial, subsequent and differential data pulls. We scope medical conversions record requirements and gain a solid understanding of the destination system data ingestion specifications. We establish clear goals, determine testing and validation plans and set expectations around the timing, effort and resource allocation it will take to hit deadlines and budget allocations.
Access is gained to the source system so that data can be extracted and imported into a more common structure for analysis and modeling. In cases where application vendors host the application, data is obtained so that data transformation can take place.
The purpose here is to determine the accuracy of the source system data, identifying potential issues, inconsistencies or duplications. During this process, we define the source data, understand its relationships, its usage, and how it’s structured compared to the destination database schema. Based on feedback from end users and stakeholders, we prepare the data to be transformed and loaded into the destination system. We address differences in data structure from the source to the destination system. Data is then modeled to fit the destination specifications for data ingestion.
Through testing, we identify issues, understand which data can be migrated and which cannot, and determine how long the migration will take (load and run times). In validation, a field-by-field comparison of the source to the destination system is conducted – from a representative sampling of records – to ensure the integrity of the data is complete and accurate.
Data is delivered in the format specified by the receiving vendor to ingest. Typical file formats in which discrete data is delivered are CCDA/CCD, CSV, XML, HL7, Flat File. FHIR is also an option.
An EMR conversion is a complex process that involves transitioning clinical data from paper files and legacy EMRs to a new electronic medical record (EMR) or electronic health record (EHR) system. When a new EMR/EHR platform is added, the legacy systems often hold clinical, financial and employee records that still must be retained to meet compliance requirements.
Medical record retention requirements in healthcare can span from seven to 30+ years or more. As EMRs or EHRs are replaced with more robust applications, there are clinical, employee and financial records housed in old systems that still must be retained. The legacy records can be moved into the new system but first will need to be converted (transformed) to meet the new system’s requirements.
Generally, it makes financial and business sense to convert the previous one to two years’ worth of records into the new system and to migrate (move) the rest to an active archive. This ensures ongoing accessibility to legacy records without the cost and complexity of a full-scale conversion.
The benefits of a medical data conversion can include improved workflows, reduced technical issues, stronger security posture and better interoperability capabilities from having medical data in a newer, more robust EHR platform.
Clinical, employee and financial records are extracted directly from the original source system or provided by another entity. The data is migrated to a modeling database where transformation work is completed against it to ensure compatibility and accuracy in the new EHR. Lastly, export deliverables are provided to the new system in the preferred format either via SFTP or on a secure physical device.
Generally, the steps for medical data conversion include:
Learn more about our enhanced way of completing data migrations, through artificial intelligence and machine learning.
A roadmap for healthcare providers engaged in determining and implementing best practices for managing legacy data.
This webinar co-presented with DrFirst covers data conversion strategies that will reduce manual data reconciliation effort through the use of AI and benefit clinicians upon go-live of an EHR transition.